381
Research Title: Enhancing the LTE-Based Intelligent Transportation System’s Performance
Author: Qadri Jamal Al-Hamarsheh, Published Year: 2021
Wireless Personal Communications, vol. 117, no. 3
Faculty: Engineering and Technology

Abstract: Intelligent transportation system is considered as one of the main features of the new generation of the wireless systems. Furthermore, both of high speed data transmission and processing play a crucial role for these generations. In this work, two main propositions have been detailed in order to attain an improvement in such intelligent systems performance and to enhance both of data transmission and processing speed. Thus, a proposed clustering algorithm will be presented for grouping mobile nodes based on their speeds besides the assignments of the head nodes that will not be updated every cycle, while the ordinary ones themselves will execute their attaching heads continuously. In order to enhance the speed of data transmission and processing, a parallel-processing technique is emphasized. This is based on a variety of wavelet baby functions to attain the target of increasing the speed with low complexity. In addition, the optimization of the transmitted power phenomenon, the Multiband orthogonal frequency division multiplexing is used to provide such privilege via the parallel processing criterion. There have been five main efficiency factors involved in this investigation; namely complementary cumulative distributions, bit rates, energy efficiency, the cluster head life time and the ordinary nodes reattaching-head average times.

Keywords: UWB-MB-OFDM · V2V · Energy efficiency · Clustering algorithm

382
Research Title: Robust Vehicular Communications Using the Fast-Frequency-Hopping-OFDM Technology and the MIMO Spatial Multiplexing
Author: Qadri Jamal Al-Hamarsheh, Published Year: 2022
International Journal of Communication Networks and Information Security (IJCNIS), vol. 14, no. 1
Faculty: Engineering and Technology

Abstract: Vehicle-to-Vehicle communication is one of the more emerging technologies in the 21st century from either the comfortable transportation or safer transportation point of view. Vehicle-to-Vehicle communication has one crucial factor, which is the huge information to be shared among vehicles, such as the position, the road data. In such situation, the accurate information sharing process is the most important factor in order to make the vehicles operating in the most feasible way. This work proposes a more robust vehicle communication system to make the existing vehicle transportation system more efficient. In this paper, we propose a fast frequency hopping orthogonal frequency division multiplexing to mitigate the Doppler spread effect on our previously published clustering benchmark. This benchmark contains both of a clustering weighting factor based stage and a multiparallel processing stage. This is in addition to modify the PHY layer of the existing IEEE 802.11p standard in order to impose Multiple Input Multiple Output for higher throughput purposes. The results show a noticeable stability compared to our previously published work. Furthermore, the results are almost exceeds the achieved results from the Lower-ID Distributed Clustering Algorithm (DCA) from both of the speed and communication range

Keywords: OFDM, Fast Frequency Hopping, V2V, Doppler Spread, Clustering Algorithm, MIMO.

383
Research Title: Autoregressive Modeling based ECG Cardiac Arrhythmias’ Database System
Author: Qadri Jamal Al-Hamarsheh, Published Year: 2022
INTERNATIONAL JOURNAL OF CIRCUITS, SYSTEMS AND SIGNAL PROCESSING, Volume 16
Faculty: Engineering and Technology

Abstract: This article proposes an ECG (electrocardiography) database system based on linear filtering, wavelet transform, PSD analysis, and adaptive AR modeling technologies to distinguish 19 ECG beat types for classification. This paper uses the Savitzky-Golay filter and wavelet transform for noise reduction, and wavelet analysis and AR modeling techniques for feature extraction to design a database system of AR coefficients describing the ECG signals with different arrhythmia types. In the experimental part of this work, the proposed algorithm performance is evaluated using an ECG dataset containing 19 different types including normal sinus rhythm, atrial premature contraction, ventricular premature contraction, ventricular tachycardia, ventricular fibrillation, supraventricular tachycardia, and other types from the MIT-BIH Arrhythmia Database. The simulation is performed in a MATLAB environment.

Keywords: AR modeling, arrhythmia classification, Discrete Wavelet Transform, ECG noise analysis, power spectral density (PSD).

384
Research Title: Productive and Sustainable H2 Production from Waste Aluminum Using Copper Oxides-Based Graphene Nanocatalysts: A Techno-Economic Analysis
Author: Firas Abdullah Obeidat, Published Year: 2022
Sustainability (MDPI), 14(22)
Faculty: Engineering and Technology

Abstract: Hydrogen has universally been considered a reliable source of future clean energy. Its energy conversion, processing, transportation, and storage are techno-economically promising for sustainable energy. This study attempts to maximize the production of H2 energy using nanocatalysts from waste aluminum chips, an abundant metal that is considered a potential storage tank of H2 energy with high energy density. The present study indicates that the use of waste aluminum chips in the production of H2 gas will be free of cost since the reaction by-product, Al2O3, is denser and can be sold at a higher price than the raw materials, which makes the production cost more efficient and feasible. The current framework investigates seven different copper oxide-based graphene nanocomposites that are synthesized by utilizing green methods and that are well-characterized in terms of their structural, morphological, and surface properties. Reduced graphene oxide (rGO) and multi-layer graphene (MLG) are used as graphene substrates for CuO and Cu2O NPs, respectively. These graphene materials exhibited extraordinary catalytic activity, while their copper oxide composites exhibited a complete reaction with feasible techno-economic production. The results revealed that the H2 production yield and rates increased twofold with the use of these nanocatalysts. The present study recommends the optimum reactor design considerations and reaction parameters that minimize water vaporization in the reaction and suggests practical solutions to quantify and separate it. Furthermore, the present study affords an economic feasibility approach to producing H2 gas that is competitive and efficient. The cost of producing 1 kg of H2 gas from waste aluminum chips is USD 6.70, which is both economically feasible and technically applicable. The unit cost of H2 gas can be steeply reduced by building large-scale plants offering mass production. Finally, the predicted approach is applicable in large, medium, and small cities that can collect industrial waste aluminum in bulk to generate large-scale energy units.

Keywords: graphene; copper oxide; waste aluminum; hydrogen production; nanocomposites; catalysts

385
Research Title: Remote Control Package for Kuka Robots using MATLAB
Author: Mohammed Bani Younis, Published Year: 2020
2020 17th International Multi-Conference on Systems, Signals & Devices (SSD), Tunis
Faculty: Engineering and Technology

Abstract: Kuka is one of the leading innovative companies in the manufacturing of industrial robots. However, they lack of direct communication with PC in order to send and receive data. To overcome this drawback, Kuka offers additional communication packages to establish the needed communication. However, this communication package requires calculating the forward and inverse kinematics or additional hardware (PLCs). Then sending the data as an XML file to the Kuka controller. This paper is dedicated to use KukaVarproxy package to establish connection between a Kuka robot and MATLAB. Thus, users can program the robot through MATLAB without using any additional software provided by Kuka (RSI, mxA). The paper focuses on developing a MATLAB package, which users can use to program the robot without requiring to use KRL. Also, the implemented functions allow the user to program the robot without the need of any mathematical information about the robot.

Keywords: Service robots , Robot kinematics , XML , Kinematics , Software , Robots , Matlab

386
Research Title: Fast detection technique for voltage unbalance in three-phase power system
Author: Mohammed Bani Younis, Published Year: 2021
International Journal of Power Electronics and Drive System (IJPEDS), 12, No. 4
Faculty: Engineering and Technology

Abstract: In this paper, the problem of voltage unbalance in the three-phase power systems is examined. A fast detection technique (FDT) is proposed to detect the voltage unbalance precisely and speedily. The well-known detection methods require more than one cycle time to detect the unbalanced voltages, whereas the proposed technique detects the unbalanced situations speedily in a discrete manner. Reducing the time duration required to detect the unbalanced voltages will enhance the dynamic response of the control system used to balance these voltages. The FDT acquires the instantaneous values of the three load voltages, calculates the sum and the space vector for these voltages at each sample, and utilizes these parameters to detect the voltage unbalance accurately within a quarter of the cycle time. A proof-of-concept simulation model for a real power system has been built. The parameters of the aqaba-qatrana-south amman (AQSA) Jordanian power system are considered in the simulation model. Also, several test cases have been conducted to test and validate the capabilities of the proposed technique.

Keywords: Power distribution; Power quality; Space vector; Voltage unbalance

387
Research Title: Economic evaluation of induction motor based on motor’s nameplate data and initial cost
Author: Mohammed Bani Younis, Published Year: 2022
International Journal of Power Electronics and Drive System (IJPEDS), 13, No.3
Faculty: Engineering and Technology

Abstract: This paper presents a practical approach to calculate the total owning cost (TOC) of a three-phase Induction Motor, which is based on the motor’s nameplate data and the purchasing price. The economic evaluation is performed considering both the induction motor electrical energy losses and its amortized annual capital cost. The proposed technique consists of three stages, where the total power losses are determined analytically in the first stage. The load loss factor (LSF) is statistically obtained to determine the total energy losses in the second stage. In the third stage, the economic evaluation was conducted. The obtained results show that the proposed approach is a helpful tool for the decision-maker when comparing the received offers from different vendors and finding the answer to the question of which offer has less TOC. Finally, the proposed method is illustrated through a numerical example and software using MATLAB was performed. Results and conclusions have been summarized and discussed.

Keywords: Annuity factor; Motors evaluation; Motors losses; Owning cost

388
Research Title: A Nonparametric Approach Trained by Metaheuristic Algorithm for Voltage Regulation in the Electrical Distribution Network Equipped by PV Farm
Author: Mohammed Bani Younis, Published Year: 2022
Journal of Electrical Engineering & Technology,
Faculty: Engineering and Technology

Abstract: The integration of the Photovoltaic (PV) systems changes the nature of the power flow in the network and causes several problems such as voltage deviation which is considered the most important issue in electrical power systems. In this work, the Augmented Grey Wolf Optimization (AGWO) algorithm and advanced nonparametric models are proposed to mitigate the voltage deviation in the distribution network equipped with a PV farm. In the first stage of the work, the AGWO calculates the optimal value of reactive power for Static Synchronous Compensator (STATCOM) to relieve the voltage deviation. This stage is applied only in the offline mode due to the delay in AGWO's dynamic response caused by its iteration process in the computation. Therefore, in the second stage, the data set of AGWO is used to train the nonparametric models; Linear Regression (LR) and Support Vector Machine (SVM) to mitigate the voltage deviation quickly in the online mode. Jordanian Sabha Distribution Network (JSDN) equipped by PV farm is considered and modeled as a real case study to validate the proposed approach. The results showed the superior ability of the proposed integrated approach to handle the voltage deviation quickly and accurately.

Keywords: Voltage Deviation; STATCOM; Optimization Algorithm; Load Flow Calculation; Prediction Algorithms.

389
Research Title: Machine Learning for Prediction Models to Mitigate the Voltage Deviation in PV-Rich Distributed Network
Author: Mohammed Bani Younis, Published Year: 2022
International Journal of Electrical and Computer Engineering (IJECE), 13, No.1
Faculty: Engineering and Technology

Abstract: The voltage deviation is one of the most crucial power quality issues that occur in electrical power systems. Renewable energy plays a vital role in electrical distribution networks due to the high economic returns. However, the presence of photovoltaic systems changes the nature of the energy flow in the grid and causes many problems such as voltage deviation. In this work, several predictive models are examined for voltage regulation in the Jordanian Sabha Distribution Network equipped with photovoltaic farms. The Augmented Grey Wolf Optimizer is used to train the different predictive models. To evaluate the performance of models, a value of one for Regression Factor and a low value for Root Mean Square Error, Mean Square Error, and Mean Absolute Error are used as standards. In addition, a comparison between nineteen predictive models has been made. The results have proved the capability of Linear Regression and the Gaussian Process to restore the bus voltages in the distribution network accurately and quickly and to solve the shortening in the voltage dynamic response caused by the iterative nature of the heuristic algorithm.

Keywords: Distribution Network, PV Farms, Voltage Regulation, Predictive Models, Augmented Grey Wolf, Optimizer

390
Research Title: Productive and Sustainable H2 Production from Waste Aluminum Using Copper Oxides-Based Graphene Nanocatalysts: A Techno-Economic Analysis
Author: Yara Hilal Haddad, Published Year: 2022
Sustainability ,
Faculty: Engineering and Technology

Abstract: Hydrogen has universally been considered a reliable source of future clean energy. Its energy conversion, processing, transportation, and storage are techno-economically promising for sustainable energy. This study attempts to maximize the production of H2 energy using nanocatalysts from waste aluminum chips, an abundant metal that is considered a potential storage tank of H2 energy with high energy density. The present study indicates that the use of waste aluminum chips in the production of H2 gas will be free of cost since the reaction by-product, Al2O3 , is denser and can be sold at a higher price than the raw materials, which makes the production cost more efficient and feasible. The current framework investigates seven different copper oxide-based graphene nanocomposites that are synthesized by utilizing green methods and that are well-characterized in terms of their structural, morphological, and surface properties. Reduced graphene oxide (rGO) and multi-layer graphene (MLG) are used as graphene substrates for CuO and Cu2O NPs, respectively. These graphene materials exhibited extraordinary catalytic activity, while their copper oxide composites exhibited a complete reaction with feasible techno-economic production. The results revealed that the H2 production yield and rates increased twofold with the use of these nanocatalysts. The present study recommends the optimum reactor design considerations and reaction parameters that minimize water vaporization in the reaction and suggests practical solutions to quantify and separate it. Furthermore, the present study affords an economic feasibility approach to producing H2 gas that is competitive and efficient. The cost of producing 1 kg of H2 gas from waste aluminum chips is USD 6.70, which is both economically feasible and technically applicable. The unit cost of H2 gas can be steeply reduced by building large-scale plants offering mass production. Finally, the predicted approach is applicable in large, medium, and small cities that can collect industrial waste aluminum in bulk to generate large-scale energy units.

Keywords: graphene; copper oxide; waste aluminum; hydrogen production; nanocomposites; catalysts